[1] "Loaded rhdf5 package"
[1] "path_out" "path_gh5" "study_name" "model_number" "subgroup" "model_type" "process1"
[8] "process2"
Plot functions:
- mplus.plot.histogram('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_male_aehplus_grip_pef.gh5',variable,bins)
- mplus.plot.scatterplot('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_male_aehplus_grip_pef.gh5',xvar,yvar)
Plot data extraction functions:
- mplus.list.variables('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_male_aehplus_grip_pef.gh5')
- mplus.get.data('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_male_aehplus_grip_pef.gh5',variable)
List of variable names to use in the following functions:
- mplus.plot.histogram
- mplus.plot.scatterplot
- mplus.get.data
Variables:
Warning in if (index == 0) {: the condition has length > 1 and only the first element will be used
# display the empirical regression equation on the graph
#http://stackoverflow.com/questions/7549694/ggplot2-adding-regression-line-equation-and-r2-on-graph
proto_scatter <- function(dsL,x, y){
g <- ggplot2::ggplot(dsL,aes_string(x=x, y=y, fill="BAGE"))+
geom_point(shape=21,size=5, alpha=.1)+
geom_smooth(aes_string(y=y), method="loess",color="black", size=1, fill="gray80", alpha=.3, na.rm=T)+
scale_fill_gradient2(low="#7fbf7b", mid="#f7f7f7", high="#af8dc3", space="Lab")+
theme(legend.position="none")+
main_theme
g
}
# proto_scatter(dsL,x="IP", y="IC")
# proto_scatter(dsL,x_name="SP", y_name="SC")
# proto_scatter(dsL,x_name="SP", y_name="IP")
#inspect data for one individual
dsL %>% dplyr::filter(id==1) %>% dplyr::select(id, BAGE, wave, time, outcome, observed, age, IP, SP, SC, IC )
id BAGE wave time outcome observed age IP SP SC IC
1 1 2.687201 1 1 physical 300 73.6872 380.4318 -34.5074 -1.765668 28.24879
2 1 2.687201 2 2 physical NA 74.6872 380.4318 -34.5074 -1.765668 28.24879
3 1 2.687201 3 NA physical NA NA 380.4318 -34.5074 -1.765668 28.24879
4 1 2.687201 4 NA physical NA NA 380.4318 -34.5074 -1.765668 28.24879
5 1 2.687201 5 NA physical NA NA 380.4318 -34.5074 -1.765668 28.24879
6 1 2.687201 6 NA physical NA NA 380.4318 -34.5074 -1.765668 28.24879
7 1 2.687201 7 NA physical NA NA 380.4318 -34.5074 -1.765668 28.24879
8 1 2.687201 1 1 cognitive 23 73.6872 380.4318 -34.5074 -1.765668 28.24879
9 1 2.687201 2 2 cognitive NA 74.6872 380.4318 -34.5074 -1.765668 28.24879
10 1 2.687201 3 NA cognitive NA NA 380.4318 -34.5074 -1.765668 28.24879
11 1 2.687201 4 NA cognitive NA NA 380.4318 -34.5074 -1.765668 28.24879
12 1 2.687201 5 NA cognitive NA NA 380.4318 -34.5074 -1.765668 28.24879
13 1 2.687201 6 NA cognitive NA NA 380.4318 -34.5074 -1.765668 28.24879
14 1 2.687201 7 NA cognitive NA NA 380.4318 -34.5074 -1.765668 28.24879
[1] 72
dsL <- get_gh5_data(file=model_list,
study = "eas",
subgroup = "female",
model_type = "aehplus",
process1 = "grip",
process2 = "pef")
Plot functions:
- mplus.plot.histogram('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_pef.gh5',variable,bins)
- mplus.plot.scatterplot('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_pef.gh5',xvar,yvar)
Plot data extraction functions:
- mplus.list.variables('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_pef.gh5')
- mplus.get.data('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_pef.gh5',variable)
List of variable names to use in the following functions:
- mplus.plot.histogram
- mplus.plot.scatterplot
- mplus.get.data
Variables:
d <- dsL[dsL$id %in% sample(unique(dsL$id), sample_size), ]
fscore_scatter(data=dsL) # create scatterplot
##grip_gait
dsL <- get_gh5_data(file=model_list,
study = "eas",
subgroup = "female",
model_type = "aehplus",
process1 = "grip",
process2 = "gait")
Plot functions:
- mplus.plot.histogram('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_gait.gh5',variable,bins)
- mplus.plot.scatterplot('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_gait.gh5',xvar,yvar)
Plot data extraction functions:
- mplus.list.variables('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_gait.gh5')
- mplus.get.data('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_grip_gait.gh5',variable)
List of variable names to use in the following functions:
- mplus.plot.histogram
- mplus.plot.scatterplot
- mplus.get.data
Variables:
d <- dsL[dsL$id %in% sample(unique(dsL$id), sample_size), ]
fscore_scatter(d) # create scatterplot
##pef_gait
dsL <- get_gh5_data(file=model_list,
study = "eas",
subgroup = "female",
model_type = "aehplus",
process1 = "pef",
process2 = "gait")
Plot functions:
- mplus.plot.histogram('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_pef_gait.gh5',variable,bins)
- mplus.plot.scatterplot('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_pef_gait.gh5',xvar,yvar)
Plot data extraction functions:
- mplus.list.variables('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_pef_gait.gh5')
- mplus.get.data('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/eas/physical/b1_female_aehplus_pef_gait.gh5',variable)
List of variable names to use in the following functions:
- mplus.plot.histogram
- mplus.plot.scatterplot
- mplus.get.data
Variables:
d <- dsL[dsL$id %in% sample(unique(dsL$id), sample_size), ]
fscore_scatter(d) # create scatterplot
#### ELSA ####
dsL <- get_gh5_data(file=model_list,
study = "elsa",
subgroup = "female",
model_type = "aehplus",
process1 = "grip",
process2 = "fev")
Plot functions:
- mplus.plot.histogram('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_fev.gh5',variable,bins)
- mplus.plot.scatterplot('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_fev.gh5',xvar,yvar)
Plot data extraction functions:
- mplus.list.variables('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_fev.gh5')
- mplus.get.data('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_fev.gh5',variable)
List of variable names to use in the following functions:
- mplus.plot.histogram
- mplus.plot.scatterplot
- mplus.get.data
Variables:
d <- dsL[dsL$id %in% sample(unique(dsL$id), sample_size), ]
fscore_scatter(data=dsL) # create scatterplot
##grip_gait
dsL <- get_gh5_data(file=model_list,
study = "elsa",
subgroup = "female",
model_type = "aehplus",
process1 = "grip",
process2 = "gait")
Plot functions:
- mplus.plot.histogram('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_gait.gh5',variable,bins)
- mplus.plot.scatterplot('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_gait.gh5',xvar,yvar)
Plot data extraction functions:
- mplus.list.variables('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_gait.gh5')
- mplus.get.data('C:/Users/koval_000/Documents/GitHub/IALSA-2015-Portland/studies/elsa/physical/b1_female_aehplus_grip_gait.gh5',variable)
List of variable names to use in the following functions:
- mplus.plot.histogram
- mplus.plot.scatterplot
- mplus.get.data
Variables:
d <- dsL[dsL$id %in% sample(unique(dsL$id), sample_size), ]
fscore_scatter(data=dsL) # create scatterplot